The second issue of the second volume of The R Journal is now available . Download complete issue Refereed articles may be downloaded individually using the links below. Table of Contents Editorial 3 Contributed Research Articles Solving Differential Equations in R Karline Soetaert, Thomas Petzoldt and R. Woodrow Setzer 5 Source
1042 search results for "regression"
Chromosome bias in R, my notebook
My goal is to develop a means of detecting chromosome bias from a human BAM file.
Because I've been working with proprietary and novel plant genomes for the last three years, I haven't had the chance to use any of the awesome UCSC-based annotational features that have been introduced and refined in Bioconductor until now. I've returned to biomedical research...
Chromosome bias in R, my notebook
My goal is to develop a means of detecting chromosome bias from a human BAM file.
Because I've been working with proprietary and novel plant genomes for the last three years, I haven't had the chance to use any of the awesome UCSC-based annotational features that have been introduced and refined in Bioconductor until now. I've returned to biomedical research...
R programming books
My sabbatical is rapidly coming to an end, and I have to start thinking more and more about teaching. Glancing over my module description for the introductory computational statistics course I teach, I noticed that it’s a bit light on recommend/background reading. In fact it has only two books: A first course in statistical programming 
Joe West vs. Bruce Froemming: A Crude Umpire LHB/RHB Bias Comparison
In my last two posts, I have tinkered with the 'gam' package to create heat maps for individual umpire strike zones. I went ahead and grabbed Joe West's data (which has a lot more pitches than Bruce Froemming in it, since Froemming's data is only from...
Machine Learning and Data Mining with R
The San Francisco Bay Area ACM runs several courses on data mining and machine learning with R. Machine Learning 101 deals primarily with supervised learning problems, and Machine Learning 102 covers unsupervised learning and fault detection. Machine Learning 101 & 102 were most recently presented by Mike Bowles & Tricia Hoffman in September, and the lecture notes and class...
Example 8.18: A Monte Carlo experiment
In recent weeks, we've explored methods to fit logistic regression models when a state of quasi-complete separation exists. We considered Firth's penalized likelihood approach, exact logistic regression, and Bayesian models using Markov chain Monte Ca...
Some quibbles about “The R Book” by Michael Crawley
A friend recently bought The R Book and I said I would tell him of problems that I’ve noticed with it. You can eavesdrop. Page 4 The word “library” is used instead of “package”. This (common) error substantially raises the blood pressure of some people — probably to an unwarranted extent. An R package is … Continue reading...
Ghcn V3 Metadata improvements
The Global Historical Climate Network (GHCN) is in it’s beta stage. On of the stated goals of the project is to improve the metadata that is provided for the station data. Over the past few months several independent volunteers have been focusing on the issue of station metadata, each with their own focus. Ron Broberg 
Using R for Introductory Statistics, Chapter 4
Chapter 4 of Using R for Introductory Statistics gets us started working with multivariate data. The question is: what are the relationships among the variables? One way to go about answering it is by pairwise comparison of variables. Another technique is to divide the data into categories by the values of some variables and...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
